Lukas Blocher, W. Mayer, Miloš Vujadinović, J. Haack, Johannes Hofele, Dusan Radovic, T. Hiller, J. Gerlach, O. Bringmann
{"title":"利用高精度汽车MEMS IMU辅以低成本传感器阵列的陀螺仪辅助里程计导航","authors":"Lukas Blocher, W. Mayer, Miloš Vujadinović, J. Haack, Johannes Hofele, Dusan Radovic, T. Hiller, J. Gerlach, O. Bringmann","doi":"10.1109/INERTIAL53425.2022.9787758","DOIUrl":null,"url":null,"abstract":"This paper examines vehicle navigation employing a redundant array of two different types of MEMS inertial sensors in combination with wheel speed sensors. We compare the position precision of a purely inertial strap-down algorithm with motion-constraints (SMC, [1]) to gyroscope-aided odometry navigation (GAO). An RTK-corrected GNSS was used in parallel to generate the reference trajectory. Initial heading of both methods was determined by a dual-antenna GNSS moving baseline setup. Across five repeated experiments with a traveled distance of 1600 m over 275 s each, GAO delivered a mean RMSE of 4.36 m, whereas SMC resulted in errors of 634 m. For GAO, we show that initial heading error was dominant compared to the influences of gyroscope noise. Determining accurate initial heading is therefore deemed crucial for applications with prolonged GNSS outages.","PeriodicalId":435781,"journal":{"name":"2022 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Gyroscope-Aided Odometry Navigation Using a Highly-Precise Automotive MEMS IMU Complemented by a Low-Cost Sensor Array\",\"authors\":\"Lukas Blocher, W. Mayer, Miloš Vujadinović, J. Haack, Johannes Hofele, Dusan Radovic, T. Hiller, J. Gerlach, O. Bringmann\",\"doi\":\"10.1109/INERTIAL53425.2022.9787758\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper examines vehicle navigation employing a redundant array of two different types of MEMS inertial sensors in combination with wheel speed sensors. We compare the position precision of a purely inertial strap-down algorithm with motion-constraints (SMC, [1]) to gyroscope-aided odometry navigation (GAO). An RTK-corrected GNSS was used in parallel to generate the reference trajectory. Initial heading of both methods was determined by a dual-antenna GNSS moving baseline setup. Across five repeated experiments with a traveled distance of 1600 m over 275 s each, GAO delivered a mean RMSE of 4.36 m, whereas SMC resulted in errors of 634 m. For GAO, we show that initial heading error was dominant compared to the influences of gyroscope noise. Determining accurate initial heading is therefore deemed crucial for applications with prolonged GNSS outages.\",\"PeriodicalId\":435781,\"journal\":{\"name\":\"2022 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL)\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INERTIAL53425.2022.9787758\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INERTIAL53425.2022.9787758","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Gyroscope-Aided Odometry Navigation Using a Highly-Precise Automotive MEMS IMU Complemented by a Low-Cost Sensor Array
This paper examines vehicle navigation employing a redundant array of two different types of MEMS inertial sensors in combination with wheel speed sensors. We compare the position precision of a purely inertial strap-down algorithm with motion-constraints (SMC, [1]) to gyroscope-aided odometry navigation (GAO). An RTK-corrected GNSS was used in parallel to generate the reference trajectory. Initial heading of both methods was determined by a dual-antenna GNSS moving baseline setup. Across five repeated experiments with a traveled distance of 1600 m over 275 s each, GAO delivered a mean RMSE of 4.36 m, whereas SMC resulted in errors of 634 m. For GAO, we show that initial heading error was dominant compared to the influences of gyroscope noise. Determining accurate initial heading is therefore deemed crucial for applications with prolonged GNSS outages.